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Abstract Adamantinomatous craniopharyngioma (ACP) is a clinically aggressive tumor without effective treatment method. Previous studies proposed a paracrine tumorigenesis model, in which oncogenic β-catenin induces senescence in pituitary stem cells and the senescent cells lead the formation of paracrine tumors through secretion of pro-tumorigenic factors. However, there lacks characterization on senescent cells in ACPs. Here, we profiled 12 ACPs with single-cell RNA and TCR-sequencing to elucidate the cellular atlas in ACPs and 3 of them were also subject to spatial sequencing to localize different subpopulations of the tumor cells. In total, we obtained the transcriptome profiles of 70,682 cells. Tumor cells, which were unambiguously identified through the cellular mutation status of the driver CTNNB1 mutations, were clustered into 6 subsets. The whorl-like cluster (WC) cells show distinct molecular features from the other tumor cells and the palisading epithelium (PE) cells consists of a proliferating subset. Other than typical PE and WC, we identified two novel subpopulations of the tumor cells. In one subpopulation, the cells express a high level of cytokines, e.g., FDCSP and S100A8/A9, and are enriched with the senescence-associated secretory phenotype (SASP) factors. Hematoxylin and eosin staining reveals that these SASP cells lack an ordered structures and their nuclei are elongated. In the other subpopulation, the cell sizes are small and they are tightly packed together with an unusual high density expressing a high level of mitochondrial genes (median 10.9%). These cells are the origin of the tumor developmental trajectories revealed by RNA velocity and pseudo-time analysis. Single-cell RNA and TCR analysis reveals that some ACPs are infiltrated with clonally expanded cytotoxic T cells. We propose a hypothesis that WC and PE are formed via different negative regulation mechanisms of the overactivated WNT/β-catenin signaling which provides a new understanding on the tumorigenesis of ACPs. The study lays a foundation for future studies on targeting senescent cells in ACPs with senolytic compounds or other therapeutic agents.

Overdependence on manual experience frequently leads to the irrational selection of orepass. Therefore, a scheduling model needs to be established to make sound decisions on orepass selection, increase the efficiency of underground rail transport, and improve production efficiency in metal mines. In this study, the −495 level of the Baixiangshan iron mine in Anhui Province is used as a research object. Orepass information, tunnel information, and historical mining, loading, and transporting data are collected. The data are then preprocessed to obtain a 130-order matrix that can describe the rail transit topology. Several vectors containing road/orepass basic information, road/orepass trajectory information, and orepass chronological material-level information are used for model training and validation. Time-series transformer graph convolutional network, which is denoted as T-TransGCN, is a temporal graph neural network that integrates orepass features, road features, and rail topology information. T-TransGCN is proposed to determine the optimal orepass selection. It enhances performance through splitting temporal features, fine-tuning the pooling layer architecture, and embedding edge features. Validated results show that (1) the T-TransGCN model is better than the Time-series multi-layer perceptron (T-MLP) and the Time-series graph convolutional network (T-GCN). The label accuracy, F1 score, and Top-3 accuracy of T-TransGCN improve by 7.33%, 17.00%, and 14.26% compared with those of T-MLP, which indicates that T-TransGCN can effectively integrate node attributes and topology information. Moreover, T-TransGCN has a relatively higher number of model parameters, more complex model structure, greater stability, and stronger fitting capability than T-GCN. (2) The addition of chronological material-level features to T-TransGCN increases its F1 score and Top-3 accuracy by 11.75% and 17.02%, while the addition of trajectory features improves them by 11.83% and 10.01%. Both new data preprocessing methods are effective in enhancing the generalization ability of T-TransGCN. The chronological material-level features help T-TransGCN understand the recent state of orepass, while the trajectory features reflect the importance of different orepasses dynamically. The trajectory features help the model understand structural information, such as the similarity of adjacent nodes or the similarity of forked nodes. (3) The addition of edge features further distinguishes orepass nodes from road nodes. The optimization of the outputs of the pooling layer helps avoid the distraction of unimportant information. When chronological features are split, the F1 score and Top-3 accuracy of T-TransGCN improve by 15.94% and 12.34%. This increment enhances the focus of the model on the chronological material-level information. The integration of the abovementioned model improvements further increases the fitting capability, generalization ability, and stability of T-TransGCN.

Abstract Background Effective identification of differentially expressed genes (DEGs) has been challenging for single-cell RNA sequencing (scRNA-seq) profiles. Many existing algorithms have high false positive rates (FPRs) and often fail to identify weak biological signals. Results We present a novel method for identifying DEGs in scRNA-seq data called RankCompV3. It is based on the comparison of relative expression orderings (REOs) of gene pairs which are determined by comparing the expression levels of a pair of genes in a set of single-cell profiles. The numbers of genes with consistently higher or lower expression levels than the gene of interest are counted in two groups in comparison, respectively, and the result is tabulated in a 3 × 3 contingency table which is tested by McCullagh’s method to determine if the gene is dysregulated. In both simulated and real scRNA-seq data, RankCompV3 tightly controlled the FPR and demonstrated high accuracy, outperforming 11 other common single-cell DEG detection algorithms. Analysis with either regular single-cell or synthetic pseudo-bulk profiles produced highly concordant DEGs with the ground-truth. In addition, RankCompV3 demonstrates higher sensitivity to weak biological signals than other methods. The algorithm was implemented using Julia and can be called in R. The source code is available at https://github.com/pathint/RankCompV3.jl . Conclusions The REOs-based algorithm is a valuable tool for analyzing single-cell RNA profiles and identifying DEGs with high accuracy and sensitivity.

Abstract Cu-Au intermetallic alloys are classic paradigms in the history of alloy theory for studying order-disorder transition, phase stability, and so on. However, density functional theory with a generalized gradient approximation (GGA) fails to describe their formation energies and Au-rich ground states, e.g., calculated formation energies are nearly 40% smaller than experimental values. In this work, we found that these discrepancies, which are also common in other Cu-transition metal (TM) intermetallic alloys, are actually caused by the fact that GGA produces Cu-3d bands with a shallower energy level than the experimental results, leading to incorrect d-d hybridizations. By using the Hubbard U correction to adjust the d-bands to the correct position, the discrepancies in GGA calculations are eliminated. Our finding that the correct d-bands position is the key to characterize Cu-TMs, which can be achieved efficiently by applying the Hubbard U correction.

Abstract. Background:. Adamantinomatous craniopharyngioma (ACP) is the commonest pediatric sellar tumor. No effective drug is available and interpatient heterogeneity is prominent. This study aimed to identify distinct molecular subgroups of ACP based on the multi-omics profiles, imaging findings, and histological features, in order to predict the response to anti-inflammatory treatment and immunotherapies. Methods:. Totally 142 Chinese cases diagnosed with craniopharyngiomas were profiled, including 119 ACPs and 23 papillary craniopharyngiomas. Whole-exome sequencing (151 tumors, including recurrent ones), RNA sequencing (84 tumors), and DNA methylome profiling (95 tumors) were performed. Consensus clustering and non-negative matrix factorization were used for subgrouping, and Cox regression were utilized for prognostic evaluation, respectively. Results:. Three distinct molecular subgroups were identified: WNT, ImA, and ImB. The WNT subgroup showed higher Wnt/β-catenin pathway activity, with a greater number of epithelial cells and more predominantly solid tumors. The ImA and ImB subgroups had activated inflammatory and interferon response pathways, with enhanced immune cell infiltration and more predominantly cystic tumors. Mitogen-activated protein kinases (MEK/MAPK) signaling was activated only in ImA samples, while IL-6 and epithelial–mesenchymal transition biomarkers were highly expressed in the ImB group, mostly consisting of children. The degree of astrogliosis was significantly elevated in the ImA group, with severe finger-like protrusions at the invasive front of the tumor. The molecular subgrouping was an independent prognostic factor, with the WNT group having longer event-free survival than ImB (Cox, P = 0.04). ImA/ImB cases were more likely to respond to immune checkpoint blockade (ICB) therapy than the WNT group (P

The leaves of spinach are delicate and easily injured during harvesting. To reduce the spinach damage rate and increase the conveyance success rate, an orderly harvester was designed and manufactured, and the key conveying parameters of the harvester were optimized by simulation and experiments. The compression damage stress of spinach was determined by compression tests. Then, a finite element simulation model for spinach clamping was established, and the influence of different clamping heights on the spinach deformation and equivalent stress were simulated and analyzed. Finally, response surface Box–Behnken experiments were conducted to optimize the combinations of the twisting angle, clamping distance, and height difference. The results of the compression tests showed that the compression damage stresses of spinach leaves, stems, and their connection points were 8.04 × 10−2 MPa, 7.85 × 10−2 MPa, and 11.63 × 10−2 MPa, respectively. The optimal clamping height of spinach for orderly conveyance was obtained to be 20 mm according to the finite element simulation. The response surface experimental results indicated that the significance order of factors affecting the extrusion force was the clamping distance, the height difference, and the twisting angle. The significance order of factors affecting the conveyance success rate was the clamping distance, the twisting angle, and the height difference. The optimal parameter combination was ae twisting angle of 60°, clamping distance of 24 mm, and a height difference of 20 cm. The experimental validation of the optimization results from the finite element simulation and response surface tests demonstrated that the extrusion force and conveyance success rate were 2.37 N and 94%, respectively, with a conveying damage rate of 3% for spinach, meeting the requirements for the low-damage and orderly harvesting of spinach.

Precise estimation of daily reference crop evapotranspiration (ET0) is critical for water resource management and agricultural irrigation optimization worldwide. In China, diverse climatic zones pose challenges for accurate ET0 prediction. Here, we evaluate the performance of a support vector machine (SVM) and its hybrid models, PSO-SVM and WOA-SVM, utilizing meteorological data spanning 1960–2020. Our study aims to identify a high-precision, low-input ET0 estimation tool. The findings indicate that the hybrid models, particularly WOA-SVM, demonstrated superior accuracy with R2 values ranging from 0.973 to 0.999 and RMSE values between 0.123 and 0.863 mm/d, outperforming the standalone SVM model with R2 values of 0.955 to 0.989 and RMSE values of 0.168 to 0.982 mm/d. The standalone SVM model showed relatively lower accuracy with R2 values of 0.822 to 0.887 and RMSE values of 0.381 to 1.951 mm/d. Notably, the WOA-SVM model, with R2 values of 0.990 to 0.992 and RMSE values of 0.092 to 0.160 mm/d, emerged as the top performer, showcasing the benefits of the whale optimization algorithm in enhancing SVM’s predictive capabilities. The PSO-SVM model also presented improved performance, especially in the temperate continental zone (TCZ), subtropical monsoon region (SMZ), and temperate monsoon zone (TMZ), when using limited meteorological data as the input. The study concludes that the WOA-SVM model is a promising tool for high-precision daily ET0 estimation with fewer meteorological parameters across the different climatic zones of China.

Summary: The rapid development of nuclear energy posed a great threat to the environment and human health. Herein, two hydroxyl-functionalized hyper-crosslinked polymers (PIHCP-1 and PIHCP-2) containing different electron active sites have been synthesized via Friedel-Crafts alkylation reaction of the polyimides. The resulting polymers showed a micro/mesoporous morphology and good thermal and chemical stability. Rely on the high porosity and multi-active sites, the PIHCPs show an ultrahigh iodine uptake capacity reached 6.73 g g−1 and the iodine removal efficiency from aqueous solution also reaches 99.7%. Kinetic analysis demonstrates that the iodine adsorption on PIHCPs was happened on the heterogeneous surfaces in the form of multilayer chemisorption. Electrostatic potential (ESP) calculation proves the great contribution of hydroxyl groups on the iodine capture performance. In addition, the iodine capture efficiency of both adsorbents can be maintained over 91% after four cyclic experiments which ensures their good recyclability for further practical applications.

Objective: The pathogenesis of depression in patients with Parkinson’s disease (PD) is poorly understood. Therefore, this study aimed to explore the changes in γ-aminobutyric acid (GABA) and glutamate plus glutamine (Glx) levels in patients with PD with or without depression determined using MEscher-GArwood Point Resolved Spectroscopy (MEGA-PRESS). Materials and methods: A total of 83 patients with primary PD and 24 healthy controls were included. Patients with PD were categorized into depressed PD (DPD, n = 19) and nondepressed PD (NDPD, n = 64) based on the 17-item Hamilton Depression Rating Scale. All participants underwent T1-weighted imaging and MEGA-PRESS sequence to acquire GABA+ and Glx values. The MEGA-PRESS sequence was conducted using 18.48 mL voxels in the left thalamus and medial frontal cortex. The GABA+, Glx, and creatine values were quantified using Gannet 3.1 software. Results: The GABA+ and Glx values were not significantly disparate between patients with PD and controls in the thalamus and medial frontal cortex. However, the levels of N-acetyl aspartate/creatine and choline/creatine in the left thalamus were significantly lower in patients with PD than in controls (P = .031, P = .009). The GABA+/Water and GABA+/Creatine in the medial frontal cortex were higher in DPD than in NDPD (P = .001, P = .004). The effects of depression on Glx or other metabolite levels were not evident, and no significant difference in metabolite values was noted in the left thalamus among all groups (P > .05). Conclusions: GABA+ levels increased in the medial frontal cortex in DPD, which may be more closely related to depressive pathology. Thus, alterations in GABAergic function in special brain structures may be related to the clinical manifestations of PD symptoms, and hence mediating this function might help in treating depression in PD.

Abstract The molecular biological differences between cyst walls and those in solid bodies are the foundation of the outcomes. In this study, the CTNNB1 mutations were confirmed by DNAsequencing; CTNNB1 expression levels were detected by PCR; the differences between solid bodies and cyst walls in proliferative capacity and tumor stem cell niches were assessed by immunohistochemistry; the effect of the residual cyst wall on recurrence was assessed by follow-up. Mutations in the CTNNB1 in the cyst wall and the solid body were identical in each case. No differences were found in the transcriptional level of CTNNB1 between the cyst walls and the solid bodies (P = 0.7619). The cyst wall showed a pathological structure similar to the solid body. Proliferative capacity of cyst walls was stronger than that of solid body (P = 0.0021), and β-catenin nuclear positive cells (cell clusters) in cyst walls were more than that in solid tumor (P = 0.0002). The retrospective 45 ACPs showed residual cyst wall was significantly associated with tumor recurrence or regrowth (P = 0.0176). Kaplan–Meier analysis showed there was a significant difference in the prognosis between GTR and STR (P

Background: Ductal carcinoma of the prostate (DCP) is a rare type of prostate cancer (PCa) with a higher degree of infiltration and worse prognosis than acinar adenocarcinoma of the prostate (ACP). Previous reports comparing DCP and ACP have not been very reliable and involved small sample sizes. Objective: To assess differences in mortality between ACP and DCP in a large-scale study. Design, setting, and participants: Data were downloaded from the Surveillance, Epidemiology, and End Results database in June 2022. Data for 823 939 patients diagnosed with PCa from 2004 to 2019 were examined, excluding cases with survival data missing or pathological types other than DCP and ACP. Outcome measurements and statistical analysis: Prognostic and risk factors for DCP were analyzed by generating a propensity score–matched cohort of DCP and ACP cases (1:5). Adjusted Cox models were constructed to determine hazard ratios (HRs) with 95% confidence intervals (CIs) for cancer-specific mortality (CSM) and overall mortality (OM) Results and limitations: A total of 822 607 cases (99.8%) has ACP and 1332 (0.2%) had DCP. In comparison to ACP, age at diagnosis was significantly lower for DCP (≤66 yr: 38.0% vs 50.7%; p

The properties of cg-N with point defects and an interface are investigated based on the first-principles method. Our results show that at 0 GPa, the stability of cavities depends on their size. A smaller cavity has higher stability than the larger case. The decomposition of N2 molecules mainly occurs on the (110) surface of the cavity. However, the decomposition process will be suppressed by applying high-pressure. For the interface constructed by (110) surfaces, N2 molecules will be released at low pressure, and polymerization of N2 molecules with surfaces is triggered by loading pressures of 80–100 Gpa, giving rise to a stable polymerized interface, which is also stable after decreasing the pressure to 0 GPa. The results indicate that the existence of polymeric nitrogen networks can enhance the polymerization of N2 molecules at low-temperature.

Résumé Contexte L’asthénozoospermiesévère ou complète est une entité rare qui peut conduire à l’infertilité masculine. Dans cette étude, nous avons exploré si les différentes étendues de l’asthénozoospermie sévère ou complète pouvaient affecter les résultats de l’injection intracytoplasmique de spermatozoïdes (ICSI), et nous avons comparé les résultats de l’ICSI obtenus avec des spermatozoïdes testiculaires à ceux obtenus avec des spermatozoïdes éjaculés chez les couples atteints d’asthénozoospermie complète. Résultats Quatre-vingt-dix-sept couples atteints d’asthénozoospermie sévère ou complète qui ont eu une ICSI entre janvier 2014 et décembre 2018 ont été inclus. Selon la catégorie de spermatozoïdes utilisée dans l’ICSI, les patients ont été classés en quatre groupes : groupe de spermatozoïdes mobiles progressifs éjaculés (groupe Ep), groupe de spermatozoïdes mobiles non progressifs éjaculés (groupe En), groupe de spermatozoïdes immobiles éjaculés (groupe Ei) et groupe de spermatozoïdestesticulaires (groupe TESE). Nous avons comparé les caractéristiques de base, le profil hormonal, les paramètres du sperme, la fécondation normale, les embryons de bonne qualité au jour 3, les embryons transférés, et les résultats de l’ICSI dans les quatre groupes. Le taux de grossesse clinique était significativement augmenté dans le groupe Ep (65,4%, P = 0,019) et le groupe TESE (63,6%, P = 0,035) par rapport à celui du groupe Ei (23,1%). Le taux de grossesse en cours dans le groupe Ei était significativement inférieur à celui du groupe Ep (23,1% contre 61,5%, P = 0,041). De plus, le taux de grossesse biochimique, le taux de grossesse en cours et le taux de naissances vivantes étaient beaucoup plus faibles dans le groupe Ei que dans le groupe TESE (30,8 % vs 63,6%,23,1 % vs 40,4 % et 23,1 % vs 40,4 %, respectivement). Conclusions Chez les couples atteints d’asthénozoospermie complète, les spermatozoïdes testiculaires devraient être préférés aux spermatozoïdes éjaculés pour obtenir un meilleur résultat en ICSI. Avec une sélection appropriée des spermatozoïdes testiculaires, l’étendue de l’asthénozoospermie sévère ou complète pourrait ne pas affecter les résultats de l’ICSI. De futures études avec des échantillons de plus grande taille sont donc justifiées pour valider ces résultats. Mots-clés Asthénozoospermie; spermatozoïdes éjaculés ; injection intracytoplasmique de spermatozoïdes (ICSI) ; infertilité masculine ; spermatozoïdes testiculaires.

Barocaloric effect, previously reported in solid-solid phase transition materials, offers a green alternative to current cooling technology. Here the authors report colossal BCE in n-alkanes associated with liquid–solid transition.

PURPOSEWe aimed to evaluate the diagnostic accuracy and safety profile of computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB) in patients with primary malignancy suspected of lung metastasis and assess possible factors associated with nondiagnostic results.METHODSAll PTNBs with core needle performed in our hospital from January 2014 to January 2019 were retrospectively reviewed. Overall, 108 cases were found to have a history of primary malignancy with suspected lung metastasis. Patient demographics, lesion characteristics, procedure techniques and complications were evaluated as predictors of overall diagnosis, final diagnosis of lung metastasis, and nondiagnostic results. Statistical analysis was performed using univariate analysis.RESULTSThe overall diagnostic accuracy of PTNB was 83.3%. Lung metastasis was found in 52.8% of PTNBs (57 of 108) and nondiagnostic results were present in 27.6% (18 of 108). Of the 18 cases with nondiagnostic results, 11 cases had a final diagnosis of lung metastasis (61.1%), yielding PTNB a sensitivity of 83.8% and specificity of 100% for the detection of lung metastasis. Smaller lesion size (p = 0.014), pneumothorax (p = 0.026), and hemoptysis (p = 0.014) were significantly associated with overall nondiagnostic results. Similarly, smaller lesion size (p = 0.047), pneumothorax (p = 0.019), high-grade pulmonary hemorrhage (p = 0.019), and hemoptysis (p = 0.012) were significantly correlated with unsuccessful biopsies in the diagnosis of lung metastasis.CONCLUSIONCT-guided core needle biopsy of the lung in patients with primary malignancy suspected of lung metastasis has a high diagnostic accuracy with acceptable complication rates. Small lesion size, pneumothorax, high-grade pulmonary hemorrhage, and hemoptysis are significantly associated with nondiagnostic results in the final diagnosis of lung metastasis. Repeat biopsy and clinical/radiological follow-up should be considered in cancer patients with nondiagnostic results due to the high probability of lung metastasis.

In this study, the silane coupling agent 3-aminopropyltriethoxysilane (APS) was used to cross-link graphene oxide (GO) to large-sized films, and further to prepare nacre-like structure graphene/aluminum (Al) composites. The results show that APS was successfully grafted onto the GO, forming large continuous GO films, which were then attached to the surface of the Al flakes by semi-powder metallurgy. After hot pressing, the graphene/Al composites had a lamellar structure consisted of reduced graphene oxide (rGO) and Al. In addition, the interface was well bonded without defects and Al4C3 phase. Compared with the pure Al prepared under the same condition, the compressive strength, maximum compression ratio and hardness of the 0.15 wt.% graphene/Al composites increased by 58%, 23% and 64.8%, respectively. The approach of cross-linking GO through chemical modification can be applied to the design of other bioinspired materials.

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment.Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups.Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state.Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

Abstract Background Melatonin has been shown with anticancer property and therapeutic potential for tumors. However, there lacks a systematic study on the molecular pathways of melatonin and its antitumor effects in gastrointestinal carcinomas. Methods Using the gene expression profiles of four cancer cell lines from three types of gastrointestinal carcinomas before and after melatonin treatment, including gastric carcinoma (GC), colorectal carcinoma (CRC) and hepatocellular carcinoma (HCC), differentially expressed genes (DEGs) and biological pathways influenced by melatonin were identified. The qRT-PCR analyses were performed to validate the effects of melatonin on 5-FU resistance-related genes in CRC. Results There were 17 pathways commonly altered by melatonin in the three cancer types, including FoxO signaling pathways enriched by the upregulated DEGs and cell cycle signaling pathways enriched by the downregulated DEGs, confirmed the dual role of melatonin to tumor growth, pro-apoptosis and anti-proliferation. DEGs upregulated in the three types of cancer tissues but reversely downregulated by melatonin were commonly enriched in RNA transport, spliceosome and cell cycle signaling pathways, which indicate that melatonin might exert antitumor effects through these pathways. Our results further showed that melatonin can downregulate the expression levels of 5-FU resistance-related genes, such as thymidylate synthase in GC and ATR, CHEK1, BAX and MYC in CRC. The qRT-PCR results demonstrated that melatonin enhanced the sensitivity of CRC 5-FU resistant cells by decreasing the expression of ATR. Conclusions Melatonin exerts the effects of pro-apoptosis and anti-proliferation on gastrointestinal carcinomas, and might increase the sensitivity of 5-FU in GC and CRC patients.

Helium is generally considered too inert to be present in giant ice planet mantles. The authors, by first-principles calculations and crystal structure searches, find stable ammonia–helium compounds at the conditions of Uranus and Neptune’s upper mantles, with possible implications in the planet composition models.

Background: More than 150 types of brain tumors have been documented. Accurate diagnosis is important for making appropriate therapeutic decisions in treating the diseases. The goal of this study is to develop a DNA methylation profile-based classifier to accurately identify various kinds of brain tumors.Methods: Thirteen datasets of DNA methylation profiles were downloaded from the Gene Expression Omnibus (GEO) database, of which GSE90496 and GSE109379 were used as the training set and the validation set, respectively, and the remaining 11 sets were used as the independent test set. The random forest algorithm was used to select the CpG sites based on the importance of the features and a multilayer perceptron (MLP) model was trained to classify the samples. Deconvolution with the debCAM package was used to explore the cellular composition difference among tumors.Results: From training datasets with 2,801 samples, 396,568 CpG sites were retained after preprocessing, of which 767 were selected as the modeling features. A three-layer MLP model was developed, which consists of 1,320 nodes in the hidden layer, to predict the histological types of brain tumors. The prediction accuracy is 99.2, 87.0, and 96.58%, respectively, on the training, validation and test sets. The results of deconvolution analysis showed that the cell proportions of different tumor subtypes were different, and it is approximately enough to distinguish different tumor entities.Conclusion: We developed a classifier that is robust for the classification of central nervous system tumors, and tried to analyze the reasons for the classification performance.

Abstract Background The amount of RNA per cell, namely the transcriptome size, may vary under many biological conditions including tumor. If the transcriptome size of two cells is different, direct comparison of the expression measurements on the same amount of total RNA for two samples can only identify genes with changes in the relative mRNA abundances, i.e., cellular mRNA concentration, rather than genes with changes in the absolute mRNA abundances. Results Our recently proposed RankCompV2 algorithm identify differentially expressed genes (DEGs) through comparing the relative expression orderings (REOs) of disease samples with that of normal samples. We reasoned that both the mRNA concentration and the absolute abundances of these DEGs must have changes in disease samples. In simulation experiments, this method showed excellent performance for identifying DEGs between normal and disease samples with different transcriptome sizes. Through analyzing data for ten cancer types, we found that a significantly higher proportion of the DEGs with absolute mRNA abundance changes overlapped or directly interacted with known cancer driver genes and anti-cancer drug targets than that of the DEGs only with mRNA concentration changes alone identified by the traditional methods. The DEGs with increased absolute mRNA abundances were enriched in DNA damage-related pathways, while DEGs with decreased absolute mRNA abundances were enriched in immune and metabolism associated pathways. Conclusions Both the mRNA concentration and the absolute abundances of the DEGs identified through REOs comparison change in disease samples in comparison with normal samples. In cancers these genes might play more important upstream roles in carcinogenesis.

About 20–30% of early-stage breast cancer patients suffer relapses after surgery. To identify such high-risk patients, many signatures have been reported, but they lack robustness in data measured on different platforms. Here, we developed a signature which is robust across multiple profiling platforms, and identified reproducible omics features characterizing metastasis of estrogen receptor (ER)-positive breast cancer from the Gene Expression Omnibus database with the aid of the signature. Based on the stable within-sample relative expression orderings (REOs), we constructed a signature consisting of five gene pairs, named 5-GPS, whose REOs were significantly correlated with relapse-free survival using the univariate Cox regression model. Using 5-GPS, patients were classified into the low-risk and high-risk groups. Patients in the high-risk group have worse survival compared to those in the low-risk group using Kaplan-Meier curve analysis with the log-rank test. Applying 5-GPS to the RNA-sequencing data of stage I-IV breast cancer samples archived in The Cancer Genome Atlas (TCGA), we found that the proportion of the high-risk patients increases with the stage. The proposed REO-based signature shows potential in identifying early-stage ER+ breast cancer patients with high risk of relapse after surgery.

Recently synthesized Kagome compounds AV _3 Sb _5 attract great attention due to the unusual coexistence of the topology, charge density wave, and superconductivity. In this work, based on the band structures for CsV _3 Sb _5 in the pristine phase, we construct an effective six-band model for the low-energy processes; utilizing the random phase approximation on the effective six-band model, we show that the $E_{1u}$ ( p wave) pairing dominates in the region of $0\lt U\lt0.32$ eV, the $A_{2g}$ ( I wave) in the region of $0.32\lt U\lt0.75$ eV and the $E_{2g}$ ( d wave) in the region of $0.75\lt U\lt1$ eV. Considering that the correlation in AV _3 Sb _5 is weak or intermediate, these results suggest that pairing symmetry is $A_{2g}$ ( I -wave) in the CsV _3 Sb _5 , which can explain some recent experiments about pairing symmetry.

Properties of pressurized MnSe were investigated based on the first-principles methods using exchange–correlation functionals of the local density approximation (generalized gradient approximation) with and without the Hubbard U correction. Our results show that the Hubbard U (U = 4 eV) correction is necessary to correctly describe the phase transition behaviors of MnSe. We found that at the static condition, phase transitions from the low-temperature phase with a NiAs-type structure (P63/mmc) to the P4/nmm phase at 50.5 GPa and further to the Pnma phase at 81 GPa are observed. However, if the transition starts from the room-temperature phase with a NaCl-type structure (Fm-3m), the transition-sequences and -pressures will be different, indicating that temperature can strongly affect the phase transition behaviors of MnSe. Furthermore, we found that pressure-induced negative charge transfer will promote spin crossover. The calculated superconducting properties of the Pnma phase indicate that it may be an unconventional superconductor.

Abstract Background Due to experimental batch effects, the application of a quantitative transcriptional signature for disease diagnoses commonly requires inter-sample data normalization, which would be hardly applicable under common clinical settings. Many cancers might have qualitative differences with the non-cancer states in the gene expression pattern. Therefore, it is reasonable to explore the power of qualitative diagnostic signatures which are robust against experimental batch effects and other random factors. Results Firstly, using data of technical replicate samples from the MicroArray Quality Control (MAQC) project, we demonstrated that the low-throughput PCR-based technologies also exist large measurement variations for gene expression even when the samples were measured in the same test site. Then, we demonstrated the critical limitation of low stability for classifiers based on quantitative transcriptional signatures in applications to individual samples through a case study using a support vector machine and a naïve Bayesian classifier to discriminate colorectal cancer tissues from normal tissues. To address this problem, we identified a signature consisting of three gene pairs for discriminating colorectal cancer tissues from non-cancer (normal and inflammatory bowel disease) tissues based on within-sample relative expression orderings (REOs) of these gene pairs. The signature was well verified using 22 independent datasets measured by different microarray and RNA_seq platforms, obviating the need of inter-sample data normalization. Conclusions Subtle quantitative information of gene expression measurements tends to be unstable under current technical conditions, which will introduce uncertainty to clinical applications of the quantitative transcriptional diagnostic signatures. For diagnosis of disease states with qualitative transcriptional characteristics, the qualitative REO-based signatures could be robustly applied to individual samples measured by different platforms.

Abstract Background It is often difficult to obtain sufficient quantity of RNA molecules for gene expression profiling under many practical situations. Amplification from low-input samples may induce artificial signals. Results We compared the expression measurements of low-input mRNA samples, from 25 pg to 1000 pg mRNA, which were amplified and profiled by Smart-seq, DP-seq and CEL-seq techniques using the Illumina HiSeq 2000 platform, with those of the paired high-input (50 ng) mRNA samples. Even with 1000 pg mRNA input, we found that thousands of genes had at least 2 folds-change of expression levels in the low-input samples compared with the corresponding paired high-input samples. Consequently, a transcriptional signature based on quantitative expression values and determined from high-input RNA samples cannot be applied to low-input samples, and vice versa. In contrast, the within-sample relative expression orderings (REOs) of approximately 90% of all the gene pairs in the high-input samples were maintained in the paired low-input samples with 1000 pg input mRNA molecules. Similar results were observed in the low-input total RNA samples amplified and profiled by the Whole-Genome DASL technique using the Illumina HumanRef-8 v3.0 platform. As a proof of principle, we developed REOs-based signatures from high-input RNA samples for discriminating cancer tissues and showed that they can be robustly applied to low-input RNA samples. Conclusions REOs-based signatures determined from the high-input RNA samples can be robustly applied to samples profiled with the low-input RNA samples, as low as the 1000 pg and 250 pg input samples but no longer stable in samples with less than 250 pg RNA input to a certain degree.

Abstract Background The Connectivity Map (CMAP) database, an important public data source for drug repositioning, archives gene expression profiles from cancer cell lines treated with and without bioactive small molecules. However, there are only one or two technical replicates for each cell line under one treatment condition. For such small-scale data, current fold-changes-based methods lack statistical control in identifying differentially expressed genes (DEGs) in treated cells. Especially, one-to-one comparison may result in too many drug-irrelevant DEGs due to random experimental factors. To tackle this problem, CMAP adopts a pattern-matching strategy to build “connection” between disease signatures and gene expression changes associated with drug treatments. However, many drug-irrelevant genes may blur the “connection” if all the genes are used instead of pre-selected DEGs induced by drug treatments. Methods We applied OneComp, a customized version of RankComp, to identify DEGs in such small-scale cell line datasets. For a cell line, a list of gene pairs with stable relative expression orderings (REOs) were identified in a large collection of control cell samples measured in different experiments and they formed the background stable REOs. When applying OneComp to a small-scale cell line dataset, the background stable REOs were customized by filtering out the gene pairs with reversal REOs in the control samples of the analyzed dataset. Results In simulated data, the consistency scores of overlapping genes between DEGs identified by OneComp and SAM were all higher than 99%, while the consistency score of the DEGs solely identified by OneComp was 96.85% according to the observed expression difference method. The usefulness of OneComp was exemplified in drug repositioning by identifying phenformin and metformin related genes using small-scale cell line datasets which helped to support them as a potential anti-tumor drug for non-small-cell lung carcinoma, while the pattern-matching strategy adopted by CMAP missed the two connections. The implementation of OneComp is available at https://github.com/pathint/reoa . Conclusions OneComp performed well in both the simulated and real data. It is useful in drug repositioning studies by helping to find hidden “connections” between drugs and diseases.

Background: Previously reported transcriptional signatures for predicting the prognosis of stage I-III bladder cancer (BLCA) patients after surgical resection are commonly based on risk scores summarized from quantitative measurements of gene expression levels, which are highly sensitive to the measurement variation and sample quality and thus hardly applicable under clinical settings. It is necessary to develop a signature which can robustly predict recurrence risk of BLCA patients after surgical resection.Methods: The signature is developed based on the within-sample relative expression orderings (REOs) of genes, which are qualitative transcriptional characteristics of the samples.Results: A signature consisting of 12 gene pairs (12-GPS) was identified in training data with 158 samples. In the first validation dataset with 114 samples, the low-risk group of 54 patients had a significantly better overall survival than the high-risk group of 60 patients (HR = 3.59, 95% CI: 1.34~9.62, p = 6.61 × 10−03). The signature was also validated in the second validation dataset with 57 samples (HR = 2.75 × 1008, 95% CI: 0~Inf, p = 0.05). Comparison analysis showed that the transcriptional differences between the low- and high-risk groups were highly reproducible and significantly concordant with DNA methylation differences between the two groups.Conclusions: The 12-GPS signature can robustly predict the recurrence risk of stage I-III BLCA patients after surgical resection. It can also aid the identification of reproducible transcriptional and epigenomic features characterizing BLCA metastasis.

To investigate the correlation of prostatic calculi (PC) with semen parameters in men with fertility intention, this retrospective case–control study enrolled 1,303 participants ranging from 20 to 59 years old; 725 were diagnosed with PC using abdominal ultrasonography. Patients with PC were classified into the type A calculi group (discrete and small echoes) and type B calculi group (coarse and large masses of multiple echoes). Five hundred and seventy-eight men without PC were recruited for the control group. The clinical data of each group were collected and analyzed. The total motility was significantly lower for subjects with type B calculi (41.84% ± 17.50%) than for subjects in the type A calculi (51.78% ± 20.84%; p < .001) and control (54.47% ± 20.74%; p < .001) groups. The percentage of progressively motile was significantly lower for the type B calculi (31.66% ± 14.68%) group than the type A calculi (40.17% ± 17.09%; p < .001) and control (41.83% ± 17.05%; p < .001) groups. The results of the hypo-osmotic swelling test yielded significantly lower percentages in the type B calculi group (59.88% ± 17.13%) than the type A calculi (65.28 ± 14.43%; p = .005) and control (66.92 ± 16.12%; p < .001) groups. The type B calculi group had a significantly higher percentage of round cell concentration than control (4.5% vs. 1.0%; p = .007) did. Small and discrete PC may not influence semen quality among adult men with fertility intention, but larger and coarser PC are associated with decreased sperm motility.

N-ethyl-N-nitrosourea (ENU) mutagenesis is a powerful tool to generate mutants on a large scale efficiently, and to discover genes with novel functions at the whole-genome level in Caenorhabditis elegans, flies, zebrafish and mice, but it has never been tried in large model animals. We describe a successful systematic three-generation ENU mutagenesis screening in pigs with the establishment of the Chinese Swine Mutagenesis Consortium. A total of 6,770 G1 and 6,800 G3 pigs were screened, 36 dominant and 91 recessive novel pig families with various phenotypes were established. The causative mutations in 10 mutant families were further mapped. As examples, the mutation of SOX10 (R109W) in pig causes inner ear malfunctions and mimics human Mondini dysplasia, and upregulated expression of FBXO32 is associated with congenital splay legs. This study demonstrates the feasibility of artificial random mutagenesis in pigs and opens an avenue for generating a reservoir of mutants for agricultural production and biomedical research.

The exploration of the vast phase space of transition metal nitrides is critical for discovering novel materials and potential technological applications. Manganese mononitride with a tetragonal structure (space group I4/mmm) was synthesized in a laser-heating diamond anvil cell, which could be quenched to ambient pressure. The bulk modulus of 173 GPa was measured using in situ high-pressure diffraction, and the axial compressibility shows that, under pressure, the a direction is much more compressible than the c direction in tetragonal MnN. DFT results with correction of the on-site repulsion (GGA + U) confirm that tetragonal MnN is energetically stable and antiferromagnetic. This study highlights the need to include on-site repulsion to understand 3d metal nitrides.

The pursuit of controlled magnetism in semiconductors has been a persisting goal in condensed matter physics. Recently, Vene (phosphorene, arsenene and antimonene) has been predicted as a new class of 2D-semiconductor with suitable band gap and high carrier mobility. In this work, we investigate the edge magnetism in zigzag puckered Vene nanoribbons (ZVNRs) based on the density functional theory. The band structures of ZVNRs show half-filled bands crossing the Fermi level at the midpoint of reciprocal lattice vectors, indicating a strong Peierls instability. To remove this instability, we consider two different mechanisms, namely, spin density wave (SDW) caused by electron-electron interaction and charge density wave (CDW) caused by electron-phonon coupling. We have found that an antiferromagnetic Mott-insulating state defined by SDW is the ground state of ZVNRs. In particular, SDW in ZVNRs displays several surprising characteristics:1) comparing with other nanoribbon systems, their magnetic moments are antiparallelly arranged at each zigzag edge and almost independent on the width of nanoribbons; 2) comparing with other SDW systems, its magnetic moments and band gap of SDW are unexpectedly large, indicating a higher SDW transition temperature in ZVNRs; 3) SDW can be effectively modified by strains and charge doping, which indicates that ZVNRs have bright prospects in nanoelectronic device.

Computational chemistry is an important tool for signal assignment of 27Al nuclear magnetic resonance spectra in order to elucidate the species of aluminum(III) in aqueous solutions. The accuracy of the popular theoretical models for computing the 27Al chemical shifts was evaluated by comparing the calculated and experimental chemical shifts in more than one hundred aluminum(III) complexes. In order to differentiate the error due to the chemical shielding tensor calculation from that due to the inadequacy of the molecular geometry prediction, single-crystal X-ray diffraction determined structures were used to build the isolated molecule models for calculating the chemical shifts. The results were compared with those obtained using the calculated geometries at the B3LYP/6-31G(d) level. The isotropic chemical shielding constants computed at different levels have strong linear correlations even though the absolute values differ in tens of ppm. The root-mean-square difference between the experimental chemical shifts and the calculated values is approximately 5 ppm for the calculations based on the X-ray structures, but more than 10 ppm for the calculations based on the computed geometries. The result indicates that the popular theoretical models are adequate in calculating the chemical shifts while an accurate molecular geometry is more critical.

In this study, both experimental and theoretical approaches, including absorption spectra, fluorescence emission spectra, 1H- and 31P-NMR, electrospray ionization mass spectrometry (ESI-MS), pH-potentiometry and theoretical approaches using the BEST & SPE computer programs were applied to study the competitive complexation between ciprofloxacin (CIP) and b-nicotinamide adenine dinucleotide phosphate (NADP) with aluminum (III) in aqueous solutions. Rank annihilation factor analysis (RAFA) was used to analyze the absorption and fluorescence emission spectra of the ligands, the binary complexes and the ternary complexes. It is found, at the mM total concentration level and pH = 7.0, the bidentate mononuclear species [Al(CIP)]2+ and [Al(NADP)] predominate in the aqueous solutions of the Al(III)-CIP and Al(III)-NADP systems, and the two complexes have similar conditional stability constants. However, the pH-potentiometry results show at the mM total concentration level and pH = 7.0, the ternary species [Al(CIP)(HNADP)] predominates in the ternary complex system. Comparing predicted NMR spectra with the experimental NMR results, it can be concluded that for the ternary complex, CIP binds to aluminum ion between the 3-carboxylic and 4-carbonyl groups, while the binding site of oxidized coenzyme II is through the oxygen of phosphate, which is linked to adenosine ribose, instead of pyrophosphate. The results also suggested CIP has the potential to be a probe molecular for the detection of NADP and the Al(III)-NADP complexes under physiological condition.

Peptides selected from phage-displayed random peptide libraries are valuable in two aspects. On one hand, these peptides are candidates for new diagnostics, therapeutics and vaccines. On the other hand, they can be used to predict the networks or sites of protein-protein interactions. MimoDB, a new repository for these peptides, was developed, in which 10,716 peptides collected from 571 publications were grouped into 1,229 sets. Besides peptide sequences, other important information, such as the target, template, library and complex structure, was also included. MimoDB can be browsed and searched through a user-friendly web interface. For computational biologists, MimoDB can be used to derive customized data sets and benchmarks, which are useful for new algorithm development and tool evaluation. For experimental biologists, their results can be searched against the MimoDB database to exclude possible target-unrelated peptides. The MimoDB database is freely accessible at http://immunet.cn/mimodb/.

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China.

The annotation of the well-studied organism, Saccharomyces cerevisiae, has been improving over the past decade while there are unresolved debates over the amount of biologically significant open reading frames (ORFs) in yeast genome. We revisited the total count of protein-coding genes in S. cerevisiae S288c genome using a theoretical approach by combining the Support Vector Machine (SVM) method with six widely used measurements of sequence statistical features. The accuracy of our method is over 99.5% in 10-fold cross-validation. Based on the annotation data in Saccharomyces Genome Database (SGD), we studied the coding capacity of all 1744 ORFs which lack experimental results and suggested that the overall number of chromosomal ORFs encoding proteins in yeast should be 6091 by removing 488 spurious ORFs. The importance of the present work lies in at least two aspects. First, cross-validation and retrospective examination showed the fidelity of our method in recognizing ORFs that likely encode proteins. Second, we have provided a web service that can be accessed at http://cobi.uestc.edu.cn/services/yeast/, which enables the prediction of protein-coding ORFs of the genus Saccharomyces with a high accuracy.

Background To evaluate the association between coexisting intracranial and extracranial carotid artery atherosclerotic diseases and ipsilateral acute cerebral infarct (ACI) in symptomatic patients by using magnetic resonance (MR) vessel wall imaging.Methods Symptomatic patients were recruited from a cross-sectional, multicentre study of Chinese Atherosclerosis Risk Evaluation (CARE-II). All patients underwent MR imaging for extracranial carotid arterial wall, intracranial artery and brain. Coexisting intracranial stenosis ≥50% and extracranial carotid artery mean wall thickness (MWT) ≥1 mm and plaque compositions at the same side were evaluated and the ipsilateral ACI was identified. The association between coexisting atherosclerotic diseases and ACI was evaluated using logistic regression.Results 351 patients were recruited. Patients with ipsilateral ACI had significantly greater prevalence of coexisting intracranial stenosis ≥50% and carotid MWT ≥1 mm (20.5% vs 4.9%, p